Pixelated Microfluidics for Drug Screening on Tumour Spheroids and Ex Vivo Microdissected Tumour Explants

Dina Dorrigiv1,2, Pierre-Alexandre Goyette2, Amélie St-Georges-Robillard1,3

  • 1Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Institut du Cancer de Montréal, Montreal, QC H2X 0A9, Canada.

Cancers
|February 25, 2023
PubMed

Insights

A novel microfluidic platform enables high-throughput drug screening using 3D tumor models. This technology improves preclinical cancer drug development by mimicking tumor architecture for more accurate response prediction.

Area of Science:

  • Oncology
  • Drug Development
  • Microfluidics

Background:

  • Anticancer drug development has low approval rates, necessitating better preclinical assays.
  • 3D tumor models offer realistic architecture but face limitations like short lifespan and low throughput.
  • Current research often relies on less predictive monolayer cell cultures.

Purpose of the Study:

  • To develop an advanced microfluidic platform for 3D tumor model drug screening.
  • To enable multiplexed reagent delivery and assessment of drug responses in various 3D tumor models.
  • To overcome the limitations of existing 3D tumor models for enhanced drug discovery.

Main Methods:

  • An open-space microfluidic platform with a pixelated chemical display was engineered.
  • The platform facilitates the formation, culture, and reagent delivery to 3D tumor models (spheroids, ex vivo fragments).
  • Contact-free delivery of up to nine different treatment conditions across 144 samples per experiment was achieved.

Main Results:

  • Proof-of-concept demonstrated by multiplexed staining of fixed and live tumor models.
  • The platform successfully assessed the response of tumor models to biological stimuli.
  • The system allows for scalable, high-throughput screening of anticancer drugs.

Conclusions:

  • The microfluidic platform enhances the utility of 3D tumor models for drug screening.
  • This technology can significantly improve the prediction of clinical drug responses in oncology.
  • Upscaling the platform promises to accelerate the development of novel cancer treatments.

Related Concept Videos